scholarly journals IN SILICO MODELING OF THE MOLECULAR STRUCTURE OF microRNAs MARKERS FOR LIVER FIBROSIS IN HEPATITIS C

2019 ◽  
Vol 48 (3) ◽  
pp. 135-147
Author(s):  
Gabriela Correia Matos de Oliveira ◽  
Raymundo Paraná ◽  
Luís Jesuino De Oliveira Andrade
Keyword(s):  
Molecular Structure ◽  
Hepatitis C ◽  
Nucleotide Sequence ◽  
Computational Biology ◽  
Hepatic Fibrosis ◽  
In Silico ◽  
Computational Simulation ◽  
Micro Rna ◽  
Nucleotide Sequence Alignment ◽  
In Silico Modeling

Molecular biology looks for evidence that microRNA (miRNAs) plays a relevant function both in the beginning and advanced stages of hepatic fibrosis (HF), and has been proposed as an additional biomarker for HF forecasting in carriers of hepatitis C virus (HCV) infection. The purpose of this study was to develop an in silico modeling of the two-dimensional (2D) molecular structure of miRNA markers for HF in carriers of HCV. A search was initially performed for the nucleotide sequence of 6 miRNAs defined as biomarkers for HF, performinga computational simulation of the molecular structure of the following miRNAs: miRNA-182, miRNA-183, miRNA-1260b, miRNA-122-3p, miRNA-378i, and miRNA-214-5p. The nucleotide sequences were chosen in the GenBank of the American National Institutes of Health genetic sequence database. The nucleotide sequence alignment was carried out with a text-based format (FASTA) tool. In the molecular modeling, the structures were built with the RNAstructure, a completely automated miRNAs structure modelling server, available through Web Servers for RNA Secondary Structure Prediction. This study presented the nucleotide sequence and the computational simulation of molecular structures for the following miRNA: miRNA-182, miRNA-183, miRNA-1260b, miRNA-122-3p, miRNA-378i, and miRNA-214-5p. The molecular structure of miRNAs markers for HF in HCV carriers, through computational biology, is essential for designing more efficient optional tools for accurate treatment.  KEY WORDS: micro-RNA; Hepatitis C; Hepatic Fibrosis; Computational Biology.

scholarly journals microRNAs Over-expressed in Diabetic Foot Ulcers Healing - Computational Modeling of Molecular Structure

2021 ◽  
Author(s):  
Luis Jesuino de Oliveira Andrade ◽  
Alcina Maria Vinhaes Bittencourt ◽  
Luis Matos de Oliveira ◽  
Gabriela Correia Matos de Oliveira
Keyword(s):  
Molecular Structure ◽  
Nucleotide Sequence ◽  
Diabetic Foot ◽  
In Silico ◽  
Molecular Model ◽  
Molecular Structures ◽  
Foot Ulcers ◽  
Diabetic Foot Ulcers ◽  
Alignment Algorithms ◽  
Treatment Objective

Background: Vasculopathy associated with diabetic neuropathy are important risk factors for the diabetic foot ulcers development. Diabetic foot ulcers is severe complication that occur in about 15% of people with diabetes, being able require hospitalization and amputation in its treatment. Objective: Design in silico the molecular structure of micro-ribonucleic acid (miRNA) over-expressed in diabetic foot ulcers healing. Method: We performed a careful search of the nucleotide sequence of 8 miRNAs over-expressed in diabetic foot ulcers, designing in silico the molecular structure of following miRNAs: miRNA-146a, miRNA-155, miRNA-132, miRNA-191, miRNA-21, miRNA-203a, miRNA-203b, and miRNA-210. The nucleotides were taken from GenBank of National Center for Biotechnology Information genetic sequence database. The sequences acquired were aligned with the Clustal W multiple alignment algorithms. The molecular modeling of structures was built using the RNAstructure, an automated miRNAs structure modelling server. Results: We showed a search for nucleotide sequence and the design of the molecular structure of following miRNA over-expressed in diabetic foot ulcers healing: miRNA-146a, miRNA-155, miRNA-132, miRNA-191, miRNA-21, miRNA-203a, miRNA-203b, and miRNA-210. We produced a tutorial on a molecular model of the 8 miRNAs overexpressed in the diabetic foot by processing in silico projection of their molecular structures. Conclusion: We show in silico secondary structures design of selected of 8 miRNAs over-expressed in diabetic foot ulcers healing by means of computational biology. Keywords: Diabetic foot ulcers; microRNA; Molecular structure.

scholarly journals Computational modeling of molecular structure of microRNA inhibitors selected against microRNA over-expressed in thyroid cancer

2021 ◽  
Author(s):  
Luis Jesuino de Oliveira Andrade ◽  
Alcina Maria Vinhaes Bittencourt ◽  
Luis Matos de Oliveira ◽  
Gabriela Correia Matos de Oliveira
Keyword(s):  
Molecular Structure ◽  
Thyroid Cancer ◽  
Nucleotide Sequence ◽  
In Silico ◽  
Structure Prediction ◽  
Secondary Structure Prediction ◽  
Malignant Neoplasm ◽  
Endocrine System ◽  
Rna Secondary Structure Prediction ◽  
Alignment Algorithms

Introduction: Thyroid cancer is the most prevalent malignant neoplasm of endocrine system and advances in thyroid molecular biology studies demonstrate that microRNAs (miRNAs) seem to play a fundamental role in tumor triggering and progression. The miRNAs inhibitors are nucleic acid-based molecules that blockade miRNAs function, making unavailable for develop their usual function, also acting as gene expression controlling molecules. Objective: To develop in silico projection of molecular structure of miRNA inhibitors against miRNA over-expressed in thyroid cancer. Methods: We conducted a search of the nucleotide sequence of 12 miRNAs already defined as inhibitors against miRNA over-expressed in thyroid cancer, realizing in silico projection of the molecular structure of following miRNAs: miRNA-101, miRNA-126, miRNA-126-3p, miRNA-141, miRNA-145, miRNA-146b, miRNA-206, miRNA-3666, miRNA-497, miRNA-539, miRNA-613, and miRNA-618. The nucleotides were selected using GenBank that is the NIH genetic sequence database. The sequences obtained were aligned with the Clustal W multiple alignment algorithms. For the molecular modeling, the structures were generated with the RNAstructure, a fully automated miRNAs structure modelling server, accessible via the Web Servers for RNA Secondary Structure Prediction. Results: We demonstrated a search for nucleotide sequence and the projection of the molecular structure of the following miRNA inhibitors against miRNA over-expressed in thyroid cancer: miRNA-101, miRNA-126, miRNA-126-3p, miRNA-141, miRNA-145, miRNA-146b, miRNA-206, miRNA-3666, miRNA-497, miRNA-539, miRNA-613, and miRNA-618. Conclusion: In this study we show in silico secondary structures projection of selected of 12 miRNA inhibitors against miRNA over-expressed in thyroid cancer through computational biology. Keywords: microRNA; nucleotide analysis; molecular structure; thyroid cancer.

In Silico Modeling as a Tool to Predict and Characterize Plant Toxicity

2020 ◽  
pp. 367-378
Author(s):  
Charles Oluwaseun Adetunji ◽  
William Peter Mitembo ◽  
Chukwuebuka Egbuna ◽  
G.M. Narasimha Rao
Keyword(s):  
In Silico ◽  
Plant Toxicity ◽  
In Silico Modeling

scholarly journals Identification of Potential HCV Inhibitors Based on the Interaction of Epigallocatechin-3-Gallate with Viral Envelope Proteins

Molecules ◽  
2021 ◽  
Vol 26 (5) ◽  
pp. 1257
Author(s):  
Fareena Shahid ◽  
Noreen ◽  
Roshan Ali ◽  
Syed Lal Badshah ◽  
Syed Babar Jamal ◽  
...  
Keyword(s):  
Hepatitis C ◽  
In Silico ◽  
Experimental Validation ◽  
Homology Modelling ◽  
Viral Envelope ◽  
Screening Methods ◽  
Binding Affinities ◽  
Autodock Vina ◽  
Potential Inhibitors ◽  
Very High

Hepatitis C is affecting millions of people around the globe annually, which leads to death in very high numbers. After many years of research, hepatitis C virus (HCV) remains a serious threat to the human population and needs proper management. The in silico approach in the drug discovery process is an efficient method in identifying inhibitors for various diseases. In our study, the interaction between Epigallocatechin-3-gallate, a component of green tea, and envelope glycoprotein E2 of HCV is evaluated. Epigallocatechin-3-gallate is the most promising polyphenol approved through cell culture analysis that can inhibit the entry of HCV. Therefore, various in silico techniques have been employed to find out other potential inhibitors that can behave as EGCG. Thus, the homology modelling of E2 protein was performed. The potential lead molecules were predicted using ligand-based as well as structure-based virtual screening methods. The compounds obtained were then screened through PyRx. The drugs obtained were ranked based on their binding affinities. Furthermore, the docking of the topmost drugs was performed by AutoDock Vina, while its 2D interactions were plotted in LigPlot+. The lead compound mms02387687 (2-[[5-[(4-ethylphenoxy) methyl]-4-prop-2-enyl-1,2,4-triazol-3-yl] sulfanyl]-N-[3(trifluoromethyl) phenyl] acetamide) was ranked on top, and we believe it can serve as a drug against HCV in the future, owing to experimental validation.

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